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MASCEM: EPEX SPOT Day-Ahead market integration and simulation

MASCEM: EPEX SPOT Day-Ahead market integration and simulatio...

引用

International Conference on Intelligent Systems Applications to Power Systems (ISAP)

作者： Gabriel Santos Ricardo Fernandes Tiago Pinto Isabel Praça Zita Vale Hugo Morais GECAD - Knowledge Engineering and Decision Support Research Center Polytechnic of Porto (ISEP/IPP) Porto Portugal Automation and Control Group Technical University of Denmark (DTU) Lyngby Denmark

The energy sector restructuring process in industrialized countries had the aim of reducing electricity prices by increasing competitiveness, and facilitate the integration of distributed energy resources. However, the complexity in market players' interactions has increased, and new problems have emerged. decision support tools that facilitate the study and comprehension of these markets became extremely useful, providing players with competitive advantage. MASCEM (Multi-Agent Simulator of Competitive Electricity Markets) arises in this context, modeling and simulating real electricity markets. It is crucial to MASCEM to have the ability to simulate as many market models and player types as possible, thus enhancing the ability to recreate the electricity markets reality in its maximum possible extent. This paper presents the EPEX Spot Day-Ahead market integration in MASCEM. EPEX Spot SE's mission is to lead European markets coupling in a single unified market, thus being crucial for the study of competitive electricity markets.

关键词： Europe Power markets Context Companies Adaptive systems Power systems

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Management of Heating, Ventilation and Air Conditioning system for SHIM platform

Management of Heating, Ventilation and Air Conditioning syst...

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IEEE PES Conference on Innovative Smart Grid Technologies (ISGT Latin America)

作者： Filipe Fernandes André Carreiro Hugo Morais Zita Vale Danilo S. Gastaldello Haroldo L. M. do Amaral André Nunes de Souza GECAD - Knowledge Engineering and Decision Support Research Center IPP - Polytechnic Institute of Porto USP - University of São Paulo - Department of Electrical Engineering Polytechnic School Department of Electrical Engineering UNESP - São Paulo State University

Several approaches have been proposed according the concepts of smart grids and the smart home is one of them. A smart home can be defined as a system with network communication between all devices allowing the control, monitoring and remote access of the management system, progressing in a generalized way of all loads for an individual way, through individual management of loads. The paper proposes a Heating, Ventilation and Air Conditioning (HVAC) management methodology to be included in the Supervisor Control and Data Acquisition House Intelligent Management (SHIM). SHIM is a simulation platform developed and implemented in the knowledge engineering and decision support research center (GECAD) to support the control and management of appliances of end consumers. The main goal of the presented work is to develop a HVAC management methodology consisting in a priority system that classifies the importance of the HVAC in each instant. The priority classification depends directly on the difference between the room temperature and the user desired temperature, in order to take measures to optimize consumption during events with power consumption limitations maintaining user comfort.

关键词： Load modeling Smart grids Temperature dependence Ventilation Temperature measurement Energy consumption Meteorology

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Multi-agent based metalearner using genetic algorithm for decision support in electricity markets

Multi-agent based metalearner using genetic algorithm for de...

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International Conference on Intelligent Systems Applications to Power Systems (ISAP)

作者： Tiago Pinto João Barreto Isabel Praça Gabriel Santos Zita Vale E. J. Solteiro Pires GECAD - Knowledge Engineering and Decision Support Research Center IPP - Polytechnic Institute of Porto Porto Portugal UTAD - Universidade de Trás-os-Montes e Alto Douro Portugal

The continuous changes in electricity markets' mechanisms and operations turn this environment into a challenging domain for the participating entities. Simulation tools are increasingly being used for decision support purposes of such entities. In particular, multi-agent based simulation, which facilitates the modeling of different types of mechanisms and players, is being fruitfully applied to the study of worldwide electricity markets. An effective decision support to market players' negotiations is, however, still not properly reached due to the uncertainty that results from the increasing penetration of renewable generation and the complexity of market mechanisms themselves. In this scope, this paper proposes a novel metalearner that provides decision support to market players in their negotiations. The proposed metalearner uses as input the output of several other market negotiation strategies, which are used to create a new, enhanced response. The final result is achieved through the combination and evolution of the strategies' learning results by applying a genetic algorithm.

关键词： Electricity supply industry Genetic algorithms Context Sociology Statistics Genetics Analytical models

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Portfolio Optimization for Electricity Market Participation with Particle Swarm

Portfolio Optimization for Electricity Market Participation ...

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International Workshop on Database and Expert Systems Applications

作者： Ricardo Faia Tiago Pinto Zita Vale E.J. Solteiro Pires GECAD - Knowledge Engineering and Decision Support Research Center Polytechnic of Porto (ISEP IIPP) Porto Portugal UTAD - Universidade de Tras-os-Montes e Alto Douro Vila Real Portugal

The liberalization of energy markets has imposed several modifications in the electricity market environment. The paradigm of monopoly market ceased to exist, and new models have been put into practice. The new models have increased the incentive on competitiveness, making market players struggle to achieve the best outcomes out of market participation. Producers aim at reaching the maximum profit on the sale of energy, while consumers try to minimize their spending on electrical energy. The proposed methodology considers the optimization of players' participation in multiple market opportunities. Reference prices that are expected in each market type at each moment are achieved through the application of neural networks. Using the forecasted prices, the proposed portfolio optimization method allocates the sale and purchase of electrical energy to different markets throughout the time, with the aim at achieving the most advantageous participation profile. A particle swarm approach is used to reduce the execution time while guaranteeing the minimum degradation of the results. Results of the swarm methodology are compared to those of a deterministic approach, using real data from the Iberian electricity market - MIBEL.

关键词： Optimization Portfolios Electricity supply industry Adaptation models Particle swarm optimization Artificial neural networks Context

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Economic Impact of Demand Response in the Scheduling of Distributed Energy Resources

Economic Impact of Demand Response in the Scheduling of Dist...

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IEEE Symposium Series on Computational Intelligence

作者： Joao Spinola Pedro Faria Zita Vale GECAD - Knowledge Engineering and Decision Support Research Center IPP - Polytechnic Institute of Porto

ISBN: (纸本)9781479975617

Demand Response (DR) allows consumers to participate in energy markets, thus assuming an active role. However, the need of an aggregator capable of managing these resources and making decisions accordingly with the objectives of such resources has not been fully addressed. The aggregator activities are complex, and therefore, in the need of intelligent support to accomplish reasonable solutions. This paper proposes a methodology to evaluate the advantages of using DR programs in the resource rescheduling while classification and regression trees are introduced to support the aggregator in terms of scheduling and tariffs definition. Often these techniques are used to help the aggregator decide, as they also learn through training. Focus is given to the use of trees to predict and decide, the consumers' prices and reduction levels to apply, respectively. The case study has 548 distributed generators, 10 external suppliers and 20310 consumers.

关键词： Demand-Responsive distributed energy resources Economic impact Consumers Energy sources DR energy market classification and regression trees Consumers

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Quantum-based particle swarm optimization application to studies of aggregated consumption shifting and generation scheduling in smart grids

Quantum-based particle swarm optimization application to stu...

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2014 IEEE Symposium Series on Computational Intelligence, IEEE SSCI 2014 - 2014 IEEE Symposium on Computational Intelligence Applications in Smart Grid, CIASG 2014

作者： Faria, Pedro Soares, Joao Vale, Zita GECAD - Knowledge Engineering and Decision Support Research Center IPP - Polytechnic Institute of Porto Porto Portugal

ISBN: (纸本)9781479945474

Demand response programs and models have been developed and implemented for an improved performance of electricity markets, taking full advantage of smart grids. Studying and addressing the consumers' flexibility and network operation scenarios makes possible to design improved demand response models and programs. The methodology proposed in the present paper aims to address the definition of demand response programs that consider the demand shifting between periods, regarding the occurrence of multi-period demand response events. The optimization model focuses on minimizing the network and resources operation costs for a Virtual Power Player. Quantum Particle Swarm Optimization has been used in order to obtain the solutions for the optimization model that is applied to a large set of operation scenarios. The implemented case study illustrates the use of the proposed methodology to support the decisions of the Virtual Power Player in what concerns the duration of each demand response event. © 2014 IEEE.

关键词： Smart power grids

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Smart Grid and Electricity Market joint Simulation using complementary Multi-Agent platforms

Smart Grid and Electricity Market joint Simulation using com...

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IEEE Eindhoven PowerTech Conference

作者： Tiago Pinto Marco Silva Gabriel Santos Luis Gomes Bruno Canizes Zita Vale GECAD - Knowledge Engineering and Decision Support Research Center Polytechnic of Porto (IPP) Porto Portugal

This paper presents an enhanced simulation platform composed by the integration of two distinct multi-agent based simulators. The two simulators are: (i) the Multi-Agent Simulator of Competitive Electricity Markets (MASCEM), which provides a simulation platform for electricity markets participation, considering scenarios based on real data from several distinct market operators;and (ii) the Multi-Agent Smart Grid Platform (MASGriP), which facilitates the simulation of smart grids and microgrids, by modeling the power network at the distribution level, and representing the main entities that act in this scope. With the cooperation between the two simulation platforms, huge studying opportunities under different perspectives are provided, resulting in an important contribution in the fields of transactive energy, electricity markets, and smart grids. A case study is presented, showing the potentialities for interaction between players of the two ecosystems, namely by demonstrating a case in which a smart grid operator, which manages the internal resources of a smart grid, is able to participate in electricity market negotiations to sell the surplus of generation in some periods of the day, and buy the necessary power to satisfy the demand of smart grid consumers in other periods of the day.

关键词： Electricity Markets Energy Resource Management Multi-Agent Simulation Smart Grid

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Multiagent system architecture for short-term operation of integrated microgrids 19

Multiagent system architecture for short-term operation of i...

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19th IFAC World Congress on International Federation of Automatic Control, IFAC 2014

作者： Ghazvini, Mohammad Ali Fotouhi Abedini, Reza Pinto, Tiago Vale, Zita GECAD - Knowledge Engineering and Decision-Support Research Center IPP - Polytechnic Institute of Porto Porto Portugal

ISBN: (纸本)9783902823625

The forthcoming smart grids are comprised of integrated microgrids operating in grid-connected and isolated mode with local generation, storage and demand response (DR) programs. The proposed model is based on three successive complementary steps for power transaction in the market environment. The first step is characterized as a microgrid's internal market;the second concerns negotiations between distinct interconnected microgrids;and finally, the third refers to the actual electricity market. The proposed approach is modeled and tested using a MAS framework directed to the study of the smart grids environment, including the simulation of electricity markets. This is achieved through the integration of the proposed approach with the MASGriP (Multi-Agent Smart Grid Platform) system. © IFAC.

关键词： Smart power grids

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The Influence of the Consumer Modelling Approach in Demand Response Programs Implementation

The Influence of the Consumer Modelling Approach in Demand R...

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IEEE Eindhoven PowerTech Conference

作者： Fabio Pereira Pedro Faria Zita Vale GECAD - Knowledge Engineering and Decision Support Research Center IPP - Polytechnic Institute of Porto Porto Portugal

The use of demand response programs brings several advantages to the power systems operators, to the consumers, as well as to the proper functioning of the whole electrical power system. The present paper proposes a methodology based on the use of five types of demand response programs (Steps, Quadratic, Constant, Linear and Elasticity). These programs corresponds to distinct approaches to model the consumer participation in demand response programs. This methodology can be used by a Virtual Power Player that aggregates and manages the small size consumers demand response for the participation in demand response programs. Distinct consumption reduction levels have been implemented in a case study composed by 218 consumers. The aggregator becomes able to discuss on the remuneration approach adequate for each reduction level and consumer type.

关键词： Demand response programs Remuneration tariffs Virtual power player

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Scheduling and Aggregation of Distributed Generators and Consumers Participating in Demand Response Programs

Scheduling and Aggregation of Distributed Generators and Con...

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IEEE Eindhoven PowerTech Conference

作者： Joao Spinola Pedro Faria Zita Vale GECAD - Knowledge Engineering and Decision-Support Research Center ISEP/IPP-Polytechnic of Porto Porto Portugal

The use of distributed generation and demand response programs in smart grids implies management and integration of these resources when they are interconnected with the main power system. In the present paper, it is defined a methodology that can be used by the Virtual Power Player in order to aggregate and schedule the resources. The aggregated producers and consumers are optimally managed, making them profitable and fully integrated in the network operation. The focus is given to the partition clustering algorithm, k-means, which is applied to several operation scenarios. The clustering of the resources is made in order to define the remuneration of each defined group, which corresponds to a distinct demand response program or remuneration group. The case study includes 20310 consumers and 548 distributed generation units, in 648 distinct operation scenarios.

关键词： Clustering Demand response Distributed energy resources Remuneration tariffs

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